LEARNING OUTCOMES
The student will get more familiar using python. The course has the following intended learning outcomes:
Reading and writing to files in different formats(Xml,Json,Csv)
Installing, importing and using packages and libraries
Use numpy, panda, scipy and matplotlib.
Get familiar with lambda, zip, map and sort.
Given a specific problem, define the input, calculation and output in pseudo-code
Clean a dataset, perform various calculations (e.g. regression) on data, present findings with appropriate diagrams.
Use vector and matrix calculations and being able to optimize the code for sparse data.
Choose which information to present and how
Credits: 3
Schedule: 28.02.2023 - 05.04.2023
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Barbara Keller
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Assessment Methods and Criteria
valid for whole curriculum period:
The final course grade consists of two parts: Graded weekly programming exercises and a graded group project
Workload
valid for whole curriculum period:
Lectures, independent work, group work & exercises
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Spring IV
2023-2024 Spring IV